The MRIQC workflows¶
The anatomical workflow¶
The anatomical workflow follows the following steps:
- Conform (reorientations, revise data types) input data and read associated metadata.
- Skull-stripping (AFNI).
- Calculate head mask –
headmsk_wf()
. - Spatial Normalization to MNI (ANTs)
- Calculate air mask above the nasial-cerebelum plane –
airmsk_wf()
. - Brain tissue segmentation (FAST).
- Extraction of IQMs –
compute_iqms()
. - Individual-reports generation –
individual_reports()
.
This workflow is orchestrated by anat_qc_workflow()
.
For the skull-stripping, we use afni_wf
from niworkflows.anat.skullstrip
:
(Source code, png, hires.png, pdf)

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mriqc.workflows.anatomical.
airmsk_wf
(name=u'AirMaskWorkflow')[source]¶ Implements the Step 1 of [Mortamet2009].
(Source code, png, hires.png, pdf)
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mriqc.workflows.anatomical.
anat_qc_workflow
(dataset, settings, mod=u'T1w', name=u'anatMRIQC')[source]¶ One-subject-one-session-one-run pipeline to extract the NR-IQMs from anatomical images
(Source code, png, hires.png, pdf)
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mriqc.workflows.anatomical.
compute_iqms
(settings, modality=u'T1w', name=u'ComputeIQMs')[source]¶ Workflow that actually computes the IQMs
(Source code, png, hires.png, pdf)
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mriqc.workflows.anatomical.
gradient_threshold
(in_file, in_segm, thresh=1.0, out_file=None)[source]¶ Compute a threshold from the histogram of the magnitude gradient image
-
mriqc.workflows.anatomical.
headmsk_wf
(name=u'HeadMaskWorkflow', use_bet=True)[source]¶ Computes a head mask as in [Mortamet2009].
(Source code, png, hires.png, pdf)
The functional workflow¶
The functional workflow follows the following steps:
- Conform (reorientations, revise data types) input data, read
associated metadata and discard non-steady state frames
(
mriqc.utils.misc.reorient_and_discard_non_steady()
). - HMC based on
3dvolreg
from AFNI –hmc_afni()
. - Skull-stripping of the time-series (AFNI) –
fmri_bmsk_workflow()
. - Calculate mean time-series, and tSNR.
- Spatial Normalization to MNI (ANTs) –
epi_mni_align()
- Extraction of IQMs –
compute_iqms()
. - Individual-reports generation –
individual_reports()
.
This workflow is orchestrated by fmri_qc_workflow()
.
-
mriqc.workflows.functional.
compute_iqms
(settings, name=u'ComputeIQMs')[source]¶ Workflow that actually computes the IQMs
(Source code, png, hires.png, pdf)
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mriqc.workflows.functional.
epi_mni_align
(name=u'SpatialNormalization', ants_nthreads=6, testing=False, resolution=2)[source]¶ Uses FSL FLIRT with the BBR cost function to find the transform that maps the EPI space into the MNI152-nonlinear-symmetric atlas.
The input epi_mean is the averaged and brain-masked EPI timeseries
Returns the EPI mean resampled in MNI space (for checking out registration) and the associated “lobe” parcellation in EPI space.
(Source code, png, hires.png, pdf)
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mriqc.workflows.functional.
fmri_bmsk_workflow
(name=u'fMRIBrainMask', use_bet=False)[source]¶ Computes a brain mask for the input fMRI dataset
(Source code, png, hires.png, pdf)
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mriqc.workflows.functional.
fmri_qc_workflow
(dataset, settings, name=u'funcMRIQC')[source]¶ The fMRI qc workflow
(Source code, png, hires.png, pdf)
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mriqc.workflows.functional.
hmc_afni
(name=u'fMRI_HMC_afni', st_correct=False, despike=False, deoblique=False, start_idx=None, stop_idx=None)[source]¶ A HMC workflow for functional scans
(Source code, png, hires.png, pdf)
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mriqc.workflows.functional.
hmc_mcflirt
(name=u'fMRI_HMC_mcflirt')[source]¶ An HMC for functional scans using FSL MCFLIRT
(Source code, png, hires.png, pdf)